Agentic AI infrastructure requires bundled models per node

SambaNova Systems argues that modern, agentic AI workloads require model bundling—running multiple models per node—rather than traditional one-model-per-node infrastructure.

• Main point: The article explains that agentic AI systems, which orchestrate multiple specialized models and tools, need infrastructure that can host, schedule, and optimize bundles of models on the same hardware node, rather than dedicating each node to a single large model.
• Background/details: It discusses how legacy AI infrastructure and cluster design (optimized around a single massive model training or inference job) fails to efficiently support multi-model, multi-agent workloads, and advocates for new systems, scheduling, and hardware-aware designs tailored for bundled models and complex AI pipelines.